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AI in Finance: Challenges, Techniques and Opportunities [article]

Longbing Cao
2021 arXiv   pre-print
We then structure and illustrate the data-driven analytics and learning of financial businesses and data.  ...  The landscapes and challenges of financial businesses and data are firstly outlined, followed by a comprehensive categorization and a dense overview of the decades of AI research in finance.  ...  Examples are identifying arbitrage trading behaviors by mining frequent and high-utility cross-market investment strategies, discovering high-frequency trading strategies, detecting periodical price or  ... 
arXiv:2107.09051v1 fatcat:g62cz4dqt5dcrbckn4lbveat3u

Decision analytics and machine learning in economic and financial systems

Qifeng Qiao, Peter A. Beling
2016 Environment Systems and Decisions  
Decision analytics may be viewed as the combined use of predictive modeling techniques (e.g., forecasting and machine learning) and prescriptive decision frameworks (e.g., optimization and simulation)  ...  Recent years have seen an explosion in decision analytics applications, driven by advances in machine learning methods and computational optimization and by massive increases in the data to which these  ...  Several illustrative HFT strategies include (1) acting as an informal or formal market-maker, (2) high-frequency relative-value trading, and (3) directional trading on news releases, order flow, or other  ... 
doi:10.1007/s10669-016-9601-x fatcat:idaougsjbvamph5lozot42dn6m

A Review on Recent Advancements in FOREX Currency Prediction

Md. Saiful Islam, Emam Hossain, Abdur Rahman, Mohammad Shahadat Hossain, Karl Andersson
2020 Algorithms  
In recent years, the foreign exchange (FOREX) market has attracted quite a lot of scrutiny from researchers all over the world.  ...  Besides, we provide some information about the FOREX market and cryptocurrency market.  ...  Introduction The foreign exchange market, also known as FOREX, is the world's biggest currency exchange market [1] with over $5.1 trillion of volume trade per day [2] .  ... 
doi:10.3390/a13080186 fatcat:pmcbxqcgsvhedep6qvkx7qmssy

Cryptocurrency Trading: A Comprehensive Survey [article]

Fan Fang, Carmine Ventre, Michail Basios, Leslie Kanthan, Lingbo Li, David Martinez-Regoband, Fan Wu
2022 arXiv   pre-print
It is therefore important to summarise existing research papers and results on cryptocurrency trading, including available trading platforms, trading signals, trading strategy research and risk management  ...  This paper provides a comprehensive survey of cryptocurrency trading research, by covering 146 research papers on various aspects of cryptocurrency trading (e.g., cryptocurrency trading systems, bubble  ...  Conclusions We provided a comprehensive overview and analysis of the research work on cryptocurrency trading. This survey presented a nomenclature of the definitions and current state of the art.  ... 
arXiv:2003.11352v5 fatcat:l7eih2yoazbq5i5lv4wh7c24ha

Cryptocurrency trading: a comprehensive survey

Fan Fang, Carmine Ventre, Michail Basios, Leslie Kanthan, David Martinez-Rego, Fan Wu, Lingbo Li
2022 Financial Innovation  
It is therefore important to summarise existing research papers and results on cryptocurrency trading, including available trading platforms, trading signals, trading strategy research and risk management  ...  This paper provides a comprehensive survey of cryptocurrency trading research, by covering 146 research papers on various aspects of cryptocurrency trading (e.g., cryptocurrency trading systems, bubble  ...  The column "Data Resolution" means latency of the data (e.g., used in the backtest) -this is useful to distinguish between high-frequency trading and low-frequency trading.  ... 
doi:10.1186/s40854-021-00321-6 fatcat:d3d2pkxy5fgcfa4s6gi4h2snua

Benchmark dataset for mid-price forecasting of limit order book data with machine learning methods

Adamantios Ntakaris, Martin Magris, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
2018 Journal of Forecasting  
Managing the prediction of metrics in high-frequency financial markets is a challenging task. An efficient way is by monitoring the dynamics of a limit order book to identify the information edge.  ...  This paper describes the first publicly available benchmark dataset of high-frequency limit order markets for mid-price prediction.  ...  ACKNOWLEDGMENT This work was supported by H2020 Project BigDataFinance MSCA-ITN-ETN 675044 (http://bigdatafinance.eu), Training for Big Data in Financial Research and Risk Management.  ... 
doi:10.1002/for.2543 fatcat:mwlf3efxwzgyrogbii7ygmmgdy

Forecast in Capital Markets

Dimitri O. Ledenyov, Viktor O. Ledenyov
2016 Social Science Research Network  
Taylor (2009) , Naranjo, Nimalendran (2000) , Ng (2000) , Ramaswamy, Samiei (2000) , Rime (2000, 2001, 2003) , Akram, Rime, Sarno (2005) , Rime, Sarno, Sojli (2006, 2007, 2010) , Schwartz (2000) , US  ...  Heath (2009) Going to the discussion on the evolution of the high frequency electronic trading in the foreign currencies exchange market, let us make a definition of the ultra high frequency electronic  ...  the changing dynamics of the foreign currencies exchange rates at the ultra high frequency electronic trading in the foreign currencies exchange markets.  ... 
doi:10.2139/ssrn.2802085 fatcat:ngsuh5uczngv7f7kkuzhgp4xcy

On the Winning Virtuous Strategies for Ultra High Frequency Electronic Trading in Foreign Currencies Exchange Markets

Dimitri O. Ledenyov, Viktor O. Ledenyov
2014 Social Science Research Network  
The discussion on the Ledenyov law on the limiting frequency (cut off frequency) for the ultra high frequency electronic trading in the foreign currencies exchange markets in conditions of the discrete  ...  Let us demonstrate that the rapid expansion of the electronic trading in the foreign exchange markets takes place in the finances in various countries, using the data analytics in Gallardo, Heath (2009  ...  leaders, who would like to learn more on the ultra high frequency electronic trading in the foreign exchange markets at an influence by the discrete information absorption processes in the diffusion -  ... 
doi:10.2139/ssrn.2560297 fatcat:b2c5xbnfrja5jiccvxmpwkkslm

Market Liquidity: Proceedings of a Workshop Held at the BIS

Bank for International Settlements
2001 Social Science Research Network  
The behaviour of prices and even the viability of markets depend on the ability of the trading mechanism to match the trading desires of sellers and buyers.  ...  Market microstructure refers to the study of the process and outcomes of exchanging assets under a specific set of rules.  ...  Graph 1 Bayesian learning Prior on V Trade Posterior on V In information-based models, the solution to this learning problem determines the prices set by market makers.  ... 
doi:10.2139/ssrn.1168055 fatcat:gk2ovkhj3namjjnqqsnglxsfsq

Algo-Trading Strategy for Intraweek Foreign Exchange Speculation Based on Random Forest and Probit Regression

Younes Chihab, Zineb Bousbaa, Marouane Chihab, Omar Bencharef, Soumia Ziti
2019 Applied Computational Intelligence and Soft Computing  
In this work, we propose an intraweek foreign exchange speculation strategy for currency markets based on a combination of technical indicators.  ...  To exit the currency market just one negative warning from Probit or Random Forest is enough. This system was used to develop dynamic portfolio trading systems.  ...  However, technological advances gave rise to new types of trading such as the trading strategies based on data mining and machine learning.  ... 
doi:10.1155/2019/8342461 fatcat:oxssropr7fe3vbjgg452hqdftm

Wave Function Method to Forecast Foreign Currencies Exchange Rates at Ultra High Frequency Electronic Trading in Foreign Currencies Exchange Markets

Dimitri O. Ledenyov, Viktor O. Ledenyov
2015 Social Science Research Network  
Literature review on high frequency electronic trading in foreign currencies exchange markets Researching the subject of interest on the high frequency electronic trading in the foreign currencies exchange  ...  The frequencies of the trade deals completion at the ultra high frequency electronic trading in the foreign currencies exchange markets; 7.  ...  Ghysels E, Jasiak J 1995 Trading patterns: Time deformation and stochastic volatality in foreign exchange markets Proceedings of the First International Conference on High Frequency Data in Finance  ... 
doi:10.2139/ssrn.2681183 fatcat:gzmmheympzdfvlki7t74yilnfa

Predicting Stock Movements: Using Multiresolution Wavelet Reconstruction and Deep Learning in Neural Networks

Lifang Peng, Kefu Chen, Ning Li
2021 Information  
Then, the deep learning in the neural network method was used to train and test the empirical data. To explain the fundamental concepts, a conceptual analysis of similar algorithms was performed.  ...  This study's primary contribution is to demonstrate the reconstruction model of the stock time series and to perform recurrent neural networks using the deep learning method.  ...  The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.  ... 
doi:10.3390/info12100388 fatcat:bis4itl6ivcu5p2af6fb3wxabm

Stock Trend Prediction Algorithm Based on Deep Recurrent Neural Network

Ruochen Lu, Muchao Lu, Yuanpeng Zhang
2021 Wireless Communications and Mobile Computing  
K -line patterns, which summarizes usable judgment experience for human researchers on the one hand and explains the prediction logic of the hybrid neural network on the other.  ...  With the return of deep learning methods to the public eye, more and more scholars and industry researchers have tried to start exploring the possibility of neural networks to solve the problem, and some  ...  Data contain a certain amount of noise due to the complexity of market dynamics.  ... 
doi:10.1155/2021/5694975 fatcat:fnseqjrt6bacfg6ej4frxe6eka

Model Uncertainty and Exchange Rate Forecasting

Roy R. P. Kouwenberg, Agnieszka Markiewicz, Ralph Verhoeks, Remco C. J. Zwinkels
2013 Social Science Research Network  
Exchange rate models with uncertain and incomplete information predict that investors focus on a small set of fundamentals that changes frequently over time.  ...  We design a model selection rule that captures the current set of fundamentals that best predicts the exchange rate.  ...  Given the high liquidity of foreign exchange markets and the relatively low quarterly rebalancing frequency of the investment strategies, it is unlikely that transaction costs will affect the results much.https  ... 
doi:10.2139/ssrn.2291394 fatcat:kslgfikfqjhc7essb27rr4a7n4

FORECASTING FOREIGN EXCHANGE RATES WITH ARTIFICIAL NEURAL NETWORKS: A REVIEW

WEI HUANG, K. K. LAI, Y. NAKAMORI, SHOUYANG WANG
2004 International Journal of Information Technology and Decision Making  
Several design factors significantly impact the accuracy of neural network forecasts. These factors include the selection of input variables, preparing data, and network architecture.  ...  Research efforts on ANNs for forecasting exchange rates are considerable. In this paper, we attempt to provide a survey of research in this area.  ...  Acknowledgement This project is supported by NSFC, CAS and the City University of Hong Kong.  ... 
doi:10.1142/s0219622004000969 fatcat:5woran6t6veidh373r6ibivfmm
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